Model based variable risk false glucose threshold alarm prevention mechanism

ABSTRACT

Methods of determining when to activate an analyte, e.g. glucose, related alarm, such as a hypoglycemia alarm, of a continuous analyte monitor is provided. Also provided are systems, devices and kits.

PRIORITY

The present application is a continuation of U.S. patent applicationSer. No. 14/128,583 filed Dec. 20, 2013, now U.S. Pat. No. 9,622,691,which claims priority to U.S. Provisional Application No. 61/553,931filed Oct. 31, 2011, entitled “Model Based Variable Risk False GlucoseThreshold Alarm Prevention Mechanism”, the disclosure of which isincorporated herein by reference for all purposes.

BACKGROUND

The detection of the level of glucose or other analytes, such aslactate, oxygen or the like, in certain individuals is vitally importantto their health. For example, the monitoring of glucose is particularlyimportant to individuals with diabetes. Diabetics may need to monitorglucose levels to determine when insulin is needed to reduce glucoselevels in their bodies or when additional glucose is needed to raise thelevel of glucose in their bodies.

Devices have been developed for continuous or automatic monitoring ofanalytes, such as glucose, in bodily fluid such as in the blood streamor in interstitial fluid. Some of these analyte measuring devices areconfigured so that at least a portion of the devices are positionedbelow a skin surface of a user, e.g., in a blood vessel or in thesubcutaneous tissue of a user.

Ease of insertion and use, including minimal user intervention andon-body size and height (or thickness) of such transcutaneous orpercutaneous medical devices that are worn on the body are important inusability, wearability, and comfort during the device usage. Moreover,for many of such medical devices that require a battery or a similarpower source to perform the device specific operations, power managementas well as shelf life is important.

SUMMARY

Embodiments include methods for determining when to activate an analytealarm of a continuous analyte monitor. The methods may include receivinginformation from the continuous analyte monitor related to the user'sanalyte concentration, wherein the information is received at a dataprocessing component. The methods may also include receiving informationthat is input by the user, and the information is related to the user'sanalyte concentration. The information that is input by the user canalso be received at the data processing component. In addition, themethods may also include that the data processing component determinesthe best-estimate (BE) of the user's analyte concentration based uponthe information from the continuous analyte monitor and information fromthe user. Further, the methods may include that at least one conditionfor activating the analyte alarm is determined by the data processingcomponent. Furthermore, if the information related to the user's analyteconcentration converges with the best-estimate of the user's analyteconcentration then the data processing component can modify the at leastone condition for activating the analyte alarm.

Embodiments further include an integrated analyte monitoring deviceassembly, that includes an analyte sensor for transcutaneous positioningthrough a skin layer and maintained in fluid contact with aninterstitial fluid under the skin layer during a predetermined timeperiod, the analyte sensor having a proximal portion and a distalportion, and sensor electronics coupled to the analyte sensor. Thesensor electronics can include the sensor electronics comprising acircuit board having a conductive layer and a sensor antenna disposed onthe conductive layer, one or more electrical contacts provided on thecircuit board and coupled with the proximal portion of the analytesensor to maintain continuous electrical communication, and a dataprocessing component provided on the circuit board and in signalcommunication with the analyte sensor. The data processing component canbe configured to execute one or more routines for processing signalsreceived from the analyte sensor, control the transmission of dataassociated with the processed signals received from the analyte sensorto a remote location using the sensor antenna in response to a requestsignal received from the remote location. The data processing componentmay be further configured to receive information from the continuousanalyte monitor related to the user's analyte concentration, receivedata from the user related to the user's analyte concentration,determine a best-estimate of the user's analyte concentration based uponthe data signal and user data received at the processor, determine atleast one condition for activating an analyte alarm, modify the at leastone condition for activating the analyte alarm if the informationrelated to the user's analyte concentration converges with thebest-estimate of the user's analyte concentration.

Additional embodiments include an integrated analyte monitoring devicethat can include a data processing component provided on the circuitboard and in signal communication with an analyte sensor. The dataprocessing component of the integrated analyte monitoring device may beconfigured to execute one or more routines for processing signalsreceived from the analyte sensor, and control the transmission of dataassociated with the processed signals received from the analyte sensorto a remote location using the sensor antenna in response to a requestsignal received from the remote location. The data processing componentmay be additionally configured to receive information from thecontinuous analyte monitor related to the user's analyte concentration,as well as data from the user related to the user's analyteconcentration. A determination of the best-estimate of the user'sanalyte concentration based upon the data signal and user data receivedat the processor, as well as at least one condition for activating ananalyte, can also be accomplished using the data processing component.Still further, the data processing component can be configured to modifythe at least one condition for activating the analyte alarm if theinformation related to the user's analyte concentration converges withthe best-estimate of the user's analyte concentration.

These and other features, objects and advantages of the presentdisclosure will become apparent to those persons skilled in the art uponreading the details of the present disclosure as more fully describedbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a data monitoring and management system such as, forexample, an analyte (e.g., glucose) monitoring system in accordance withcertain embodiments of the present disclosure;

FIG. 2 is a graphical representation of a glucose profile showing auser's glucose level measured using a CGM sensor as a function of time,and also depicting the variation of the glucose level as a function ofcarbohydrate intake and insulin administration;

FIG. 3 is a schematic diagram of a continuous glucose monitor basedsubsystem, illustrated in terms of a state machine;

FIG. 4 is a schematic diagram of a glucose level based subsystemillustrated in terms of a state machine coupled to the continuousglucose monitor subsystem FIG. 3; and

FIGS. 5A and 5B are schematic diagrams of an embodiment of thedisclosure wherein the continuous glucose monitor and glucose levelstate machines are coupled to a stronger degree than the embodimentsshown in FIGS. 3 and 4, and also showing an additional delay timerasserted after glucose level confirmation.

INCORPORATION BY REFERENCE

Patents, applications and/or publications described herein, includingthe following patents, applications and/or publications are incorporatedherein by reference for all purposes: U.S. Pat. Nos. 4,545,382,4,711,245, 5,262,035, 5,262,305, 5,264,104, 5,320,715, 5,356,786,5,509,410, 5,543,326, 5,593,852, 5,601,435, 5,628,890, 5,820,551,5,822,715, 5,899,855, 5,918,603, 6,071,391, 6,103,033, 6,120,676,6,121,009, 6,134,461, 6,143,164, 6,144,837, 6,161,095, 6,175,752,6,270,455, 6,284,478, 6,299,757, 6,338,790, 6,377,894, 6,461,496,6,503,381, 6,514,460, 6,514,718, 6,540,891, 6,560,471, 6,579,690,6,591,125, 6,592,745, 6,600,997, 6,605,200, 6,605,201, 6,616,819,6,618,934, 6,650,471, 6,654,625, 6,676,816, 6,730,200, 6,736,957,6,746,582, 6,749,740, 6,764,581, 6,773,671, 6,881,551, 6,893,545,6,932,892, 6,932,894, 6,942,518, 7,041,468, 7,167,818, 7,299,082, and7,866,026, and U.S. Patent Publication Nos. 2004/0186365, now U.S. Pat.No. 7,811,231, 2005/0182306, now U.S. Pat. No. 8,771,183, 2006/0025662,now U.S. Pat. No. 7,740,581, 2006/0091006, 2007/0056858, now U.S. Pat.No. 8,298,389, 2007/0068807, now U.S. Pat. No. 7,846,311, 2007/0095661,2007/0108048, now U.S. Pat. No. 7,918,975, 2007/0199818, now U.S. Pat.No. 7,811,430, 2007/0227911, now U.S. Pat. No. 7,887,682, 2007/0233013,2008/0066305, now U.S. Pat. No. 7,895,740, 2008/0081977, now U.S. Pat.No. 7,618,369, 2008/0102441, now U.S. Pat. No. 7,822,557, 2008/0148873,now U.S. Pat. No. 7,802,467, 2008/0161666, 2008/0267823, 2009/0054748,now U.S. Pat. No. 7,885,698, 2009/0294277, 2010/0213057, 2010/0081909,now U.S. Pat. No. 8,219,173, 2009/0247857, now U.S. Pat. No. 8,346,335,2011/0106126, 2011/0082484, 2010/0326842, 2010/0198034, 2010/0324392,now U.S. Pat. No. 9,402,544, 2010/0230285, 2010/0313105, now U.S. Pat.No. 8,595,607, 2011/0213225, 2011/0021889, 2011/0193704, now U.S. Pat.No. 8,514,086, 2011/0190603, 2010/0317952, now U.S. Pat. No. 9,579,456,2011/0191044, now U.S. Pat. No. 9,351,669, 2011/0257495, now U.S. Pat.No. 8,965,477, 2011/0288574, now U.S. Pat. No. 9,265,453, 2011/0319729,now U.S. Pat. No. 9,215,992, and 2012/0010642, now U.S. Pat. No.9,186,098.

DETAILED DESCRIPTION

Within the scope of the present disclosure, there are provided devices,systems, kits and methods for providing compact, low profile, on-bodyphysiological parameter monitoring device (physiological parameters suchas for example, but not limited to analyte levels, temperature levels,heart rate, etc), configured for single or multiple use over apredetermined time period, which provide a low profile geometry,effective power management, improved shelf life, and ease and comfort ofuse including device positioning, and activation. Embodiments include anon-body assembly including a transcutaneously positioned analyte sensorand sensor electronics in a compact, low profile integrated assembly andcoupled to an insertion device for deployment.

Before the present disclosure is described in additional detail, it isto be understood that this disclosure is not limited to particularembodiments described, as such may, of course, vary. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting, since the scope of the present disclosure will be limited onlyby the appended claims.

Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimit of that range and any other stated or intervening value in thatstated range, is encompassed within the disclosure. The upper and lowerlimits of these smaller ranges may independently be included in thesmaller ranges is also encompassed within the disclosure, subject to anyspecifically excluded limit in the stated range. Where the stated rangeincludes one or both of the limits, ranges excluding either or both ofthose included limits are also included in the disclosure.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this disclosure belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present disclosure, the preferredmethods and materials are now described. All publications mentionedherein are incorporated herein by reference to disclose and describe themethods and/or materials in connection with which the publications arecited.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an”, and “the” include plural referents unless thecontext clearly dictates otherwise.

The publications discussed herein are provided solely for theirdisclosure prior to the filing date of the present application. Nothingherein is to be construed as an admission that the present disclosure isnot entitled to antedate such publication by virtue of prior disclosure.Further, the dates of publication provided may be different from theactual publication dates which may need to be independently confirmed.

As will be apparent to those of skill in the art upon reading thisdisclosure, each of the individual embodiments described and illustratedherein has discrete components and features which may be readilyseparated from or combined with the features of any of the other severalembodiments without departing from the scope or spirit of the presentdisclosure.

The figures shown herein are not necessarily drawn to scale, with somecomponents and features being exaggerated for clarity.

Generally, embodiments of the present disclosure relate to methods anddevices for detecting at least one analyte, such as glucose, in bodyfluid. In certain embodiments, the present disclosure relates to thecontinuous and/or automatic in vivo monitoring of the level of ananalyte using an analyte sensor.

Accordingly, embodiments include analyte monitoring devices and systemsthat include an analyte sensor—at least a portion of which ispositionable beneath the skin of the user—for the in vivo detection ofan analyte, such as glucose, lactate, and the like, in a body fluid.Embodiments include wholly implantable analyte sensors and analytesensors in which only a portion of the sensor is positioned under theskin and a portion of the sensor resides above the skin, e.g., forcontact to a transmitter, receiver, transceiver, processor, etc. Thesensor may be, for example, subcutaneously positionable in a patient forthe continuous or periodic monitoring of a level of an analyte in apatient's interstitial fluid.

For the purposes of this description, continuous monitoring and periodicmonitoring will be used interchangeably, unless noted otherwise.Discrete monitoring as used herein includes the acquisition or receptionof monitored analyte data where real time monitored analyte levelinformation is received or acquired on demand or in response to arequest to an analyte monitoring device including sensor and sensorelectronics. That is, embodiments include analyte sensors and sensorelectronics which sample and process analyte related information basedon a programmed or programmable schedule such as every minute, everyfive minutes and so on. Such analyte monitoring routines may be reportedor transmitted in real time to a receiver unit/reader device at the timeof data sampling and processing. Alternatively, as discussed, thecontinuously sampled analyte data and processed analyte related signalsmay be stored and transmitted to a remote location such as the receiverunit, data processing module, the data processing terminal, the readerdevice or the remote terminal in response to a request for suchinformation from the remote location. The analyte level may becorrelated and/or converted to analyte levels in blood or other fluids.In certain embodiments, an analyte sensor may be positioned in contactwith interstitial fluid to detect the level of glucose, and the detectedglucose may be used to infer the glucose level in the patient'sbloodstream. Analyte sensors may be insertable into a vein, artery, orother portion of the body containing fluid. Embodiments of the analytesensors of the subject disclosure may be configured for monitoring thelevel of the analyte over a time period which may range from minutes,hours, days, weeks, or longer.

Of interest are analyte sensors, such as glucose sensors, that arecapable of in vivo detection of an analyte for about one hour or more,e.g., about a few hours or more, e.g., about a few days of more, e.g.,about three or more days, e.g., about five days or more, e.g., aboutseven days or more, e.g., about several weeks or at least one month.Future analyte levels may be predicted based on information obtained,e.g., the current analyte level at time t₀, the rate of change of theanalyte, etc. Predictive alarms may notify the user of predicted analytelevels that may be of concern prior in advance of the analyte levelreaching the future level. This enables the user an opportunity to takecorrective action. Embodiments include transmission of the acquired realtime analyte information on-demand from the user (using for example, thereader device/receiver unit positioned in close proximity to the lowprofile on-body patch device), storage of the acquired real time analyteinformation, and subsequent transmission based on retrieval from thestorage device (such as a memory device).

FIG. 1 shows an exemplary in vivo-based analyte monitoring system 100 inaccordance with embodiments of the present disclosure. As shown, incertain embodiments, analyte monitoring system 100 includes on bodyelectronics 110 electrically coupled to in vivo analyte sensor 101 (aproximal portion of which is shown in FIG. 1) and attached to adhesivelayer 140 for attachment on a skin surface on the body of a user. Onbody electronics 110 includes on body housing 119, that defines aninterior compartment. Also shown in FIG. 1 is insertion device 150 that,when operated, transcutaneously positions a portion of analyte sensor101 through a skin surface and in fluid contact with ISF, and positionson body electronics 110 and adhesive layer 140 on a skin surface. Incertain embodiments, on body electronics 110, analyte sensor 101 andadhesive layer 140 are sealed within the housing of insertion device 150before use, and in certain embodiments, adhesive layer 140 is alsosealed within the housing or itself provides a terminal seal of theinsertion device 150. Devices, systems and methods that may be used withembodiments herein are described, e.g., in U.S. patent application Ser.No. 12/698,129, now U.S. Pat. No. 9,402,544, Ser. No. 13/071,461, nowU.S. Pat. No. 9,215,992, Ser. No. 13/071,487, now U.S. Pat. No.9,265,453, and Ser. No. 13/071,497, now U.S. Pat. No. 9,186,098, thedisclosures of each of which are incorporated herein by reference forall purposes.

Referring back to the FIG. 1, analyte monitoring system 100 includesdisplay device 120 or receiver/reader unit, which includes a display 122to output information to the user, an input component 121 such as abutton, actuator, a touch sensitive switch, a capacitive switch,pressure sensitive switch, jog wheel or the like, to input data orcommand to display device 120 or otherwise control the operation ofdisplay device 120. It is noted that some embodiments may includedisplay-less devices or devices without any user interface components.These devices may be functionalized to store data as a data loggerand/or provide a conduit to transfer data from on body electronicsand/or a display-less device to another device and/or location.Embodiments will be described herein as display devices for exemplarypurposes which are in no way intended to limit the embodiments of thepresent disclosure. It will be apparent that display-less devices mayalso be used in certain embodiments.

In certain embodiments, on body electronics 110 may be configured tostore some or all of the monitored analyte related data received fromanalyte sensor 101 in a memory during the monitoring time period, andmaintain it in memory until the usage period ends. In such embodiments,stored data is retrieved from on body electronics 110 at the conclusionof the monitoring time period, for example, after removing analytesensor 101 from the user by detaching on body electronics 110 from theskin surface where it was positioned during the monitoring time period.In such data logging configurations, real time monitored analyte levelis not communicated to display device 120 during the monitoring periodor otherwise transmitted from on body electronics 110, but rather,retrieved from on body electronics 110 after the monitoring time period.

In certain embodiments, input component 121 of display device 120 mayinclude a microphone and display device 120 may include softwareconfigured to analyze audio input received from the microphone, suchthat functions and operation of the display device 120 may be controlledby voice commands. In certain embodiments, an output component ofdisplay device 120 includes a speaker for outputting information asaudible signals. Similar voice responsive components such as a speaker,microphone and software routines to generate, process and store voicedriven signals may be provided to on body electronics 110.

In certain embodiments, display 122 and input component 121 may beintegrated into a single component, for example a display that candetect the presence and location of a physical contact touch upon thedisplay such as a touch screen user interface. In such embodiments, theuser may control the operation of display device 120 by utilizing a setof pre-programmed motion commands, including, but not limited to, singleor double tapping the display, dragging a finger or instrument acrossthe display, motioning multiple fingers or instruments toward oneanother, motioning multiple fingers or instruments away from oneanother, etc. In certain embodiments, a display includes a touch screenhaving areas of pixels with single or dual function capacitive elementsthat serve as LCD elements and touch sensors.

Display device 120 also includes data communication port 123 for wireddata communication with external devices such as remote terminal(personal computer) 170, for example. Example embodiments of the datacommunication port 123 include USB port, mini USB port, RS-232 port,Ethernet port, FireWire (IEEE 1394) port, or other similar datacommunication ports configured to connect to the compatible data cables.Display device 120 may also include an integrated in vitro glucosemeter, including in vitro test strip port 124 to receive an in vitroglucose test strip for performing in vitro blood glucose measurements.

Referring still to FIG. 1, display 122 in certain embodiments isconfigured to display a variety of information—some or all of which maybe displayed at the same or different time on display 122. In certainembodiments the displayed information is user-selectable so that a usercan customize the information shown on a given display screen. Display122 may include but is not limited to graphical display 138, forexample, providing a graphical output of glucose values over a monitoredtime period (which may show important markers such as meals, exercise,sleep, heart rate, blood pressure, etc), a numerical display 132, forexample, providing monitored glucose values (acquired or received inresponse to the request for the information), and trend or directionalarrow display 131 that indicates a rate of analyte change and/or a rateof the rate of analyte change, e.g., by moving locations on display 122.Additionally, display 122 may include an alarm display that annunciates.

As further shown in FIG. 1, display 122 may also include date display135 providing for example, date information for the user, time of dayinformation display 139 providing time of day information to the user,battery level indicator display 133 which graphically shows thecondition of the battery (rechargeable or disposable) of the displaydevice 120, sensor calibration status icon display 134 for example, inmonitoring systems that require periodic, routine or a predeterminednumber of user calibration events, notifying the user that the analytesensor calibration is necessary, audio/vibratory settings icon display136 for displaying the status of the audio/vibratory output or alarmstate, and wireless connectivity status icon display 137 that providesindication of wireless communication connection with other devices suchas on body electronics, data processing module 160, and/or remoteterminal 170. As additionally shown in FIG. 1, display 122 may furtherinclude simulated touch screen button 125, 126 for accessing menus,changing display graph output configurations or otherwise forcontrolling the operation of display device 120.

Referring back to FIG. 1, in certain embodiments, display 122 of displaydevice 120 may be additionally, or instead of visual display, configuredto output alarm notifications such as alarm and/or alert notifications,glucose values etc, which may be audible, tactile, or any combinationthereof. In one aspect, the display device 120 may include other outputcomponents such as a speaker, vibratory output component and the like toprovide audible and/or vibratory output indication to the user inaddition to the visual output indication provided on display 122.Further details and other display embodiments can be found in, e.g.,U.S. patent application Ser. No. 12/871,901, now U.S. Pat. No.8,514,086, and U.S. Provisional Application Nos. 61/238,672, 61/247,541,61/297,625, the disclosures of each of which are incorporated herein byreference for all purposes.

After the positioning of on body electronics 110 on the skin surface andanalyte sensor 101 in vivo to establish fluid contact with ISF (or otherappropriate body fluid), on body electronics 110 in certain embodimentsis configured to wirelessly communicate analyte related data (such as,for example, data corresponding to monitored analyte level and/ormonitored temperature data, and/or stored historical analyte relateddata) when on body electronics 110 receives a command or request signalfrom display device 120. In certain embodiments, on body electronics 110may be configured to at least periodically broadcast real time dataassociated with a monitored analyte level received by display device120, when display device 120 is within communication range of the databroadcast from on body electronics 110, i.e., it does not need a commandor request from display device 120 to send information.

For example, when within a communication range, display device 120 maybe configured to automatically transmit one or more commands to on bodyelectronics 110 to initiate data transfer, and in response, on bodyelectronics 110 may be configured to wirelessly transmit stored analyterelated data collected during the monitoring time period to displaydevice 120. In certain embodiments, the data transfer may be userinitiated. Display device 120 may in turn be connected to a remoteterminal 170, such as a personal computer, and functions as a dataconduit to transfer the stored analyte level information from the onbody electronics 110 to remote terminal 170. In certain embodiments, thereceived data from the on body electronics 110 may be stored(permanently or temporarily) in one or more memory of the display device120. In certain other embodiments, display device 120 is configured as adata conduit to pass the data received from on body electronics 110 toremote terminal 170 that is connected to display device 120.

Referring still to FIG. 1, also shown in analyte monitoring system 100are data processing module 160 and remote terminal 170. Remote terminal170 may include a personal computer, a server terminal, a laptopcomputer or other suitable data processing devices including softwarefor data management and analysis and communication with the componentsin the analyte monitoring system 100. For example, remote terminal 170may be connected to a local area network (LAN), a wide area network(WAN), or other data network for uni-directional or bi-directional datacommunication between remote terminal 170 and display device 120 and/ordata processing module 160.

Remote terminal 170 in certain embodiments may include one or morecomputer terminals located at a physician's office or a hospital. Forexample, remote terminal 170 may be located at a location other than thelocation of display device 120. Remote terminal 170 and display device120 could be in different rooms or different buildings. Remote terminal170 and display device 120 could be at least about one mile apart, e.g.,at least about 10 miles apart, e.g., at least about 100 miles apart. Forexample, remote terminal 170 could be in the same city as display device120, remote terminal 170 could be in a different city than displaydevice 120, remote terminal 170 could be in the same state as displaydevice 120, remote terminal 170 could be in a different state thandisplay device 120, remote terminal 170 could be in the same country asdisplay device 120, or remote terminal 170 could be in a differentcountry than display device 120, for example.

In certain embodiments, a separate, optional datacommunication/processing device such as data processing module 160 maybe provided in analyte monitoring system 100. Data processing module 160may include components to communicate using one or more wirelesscommunication protocols such as, for example, but not limited to,infrared (IR) protocol, Bluetooth® protocol, Zigbee® protocol, and802.11 wireless LAN protocol. Additional description of communicationprotocols including those based on Bluetooth® protocol and/or Zigbee®protocol can be found in U.S. Patent Publication No. 2006/0193375incorporated herein by reference for all purposes. Data processingmodule 160 may further include communication ports, drivers orconnectors to establish wired communication with one or more of displaydevice 120, on body electronics 110, or remote terminal 170 including,for example, but not limited to USB connector and/or USB port, Ethernetconnector and/or port, FireWire (IEEE 1394) connector and/or port, orRS-232 port and/or connector.

In certain embodiments, data processing module 160 is programmed totransmit a polling or query signal to on body electronics 110 at apredetermined time interval (e.g., once every minute, once every fiveminutes, or the like), and in response, receive the monitored analytelevel information from on body electronics 110. Data processing module160 stores in its memory the received analyte level information, and/orrelays or retransmits the received information to another device such asdisplay device 120. More specifically in certain embodiments, dataprocessing module 160 may be configured as a data relay device toretransmit or pass through the received analyte level data from on bodyelectronics 110 to display device 120 or a remote terminal (for example,over a data network such as a cellular or WiFi data network) or both.

In certain embodiments, on body electronics 110 and data processingmodule 160 may be positioned on the skin surface of the user within apredetermined distance of each other (for example, about 1-12 inches, orabout 1-10 inches, or about 1-7 inches, or about 1-5 inches) such thatperiodic communication between on body electronics 110 and dataprocessing module 160 is maintained. Alternatively, data processingmodule 160 may be worn on a belt or clothing item of the user, such thatthe desired distance for communication between the on body electronics110 and data processing module 160 for data communication is maintained.In a further aspect, the housing of data processing module 160 may beconfigured to couple to or engage with on body electronics 110 such thatthe two devices are combined or integrated as a single assembly andpositioned on the skin surface. In further embodiments, data processingmodule 160 is detachably engaged or connected to on body electronics 110providing additional modularity such that data processing module 160 maybe optionally removed or reattached as desired.

Referring again to FIG. 1, in certain embodiments, data processingmodule 160 is programmed to transmit a command or signal to on bodyelectronics 110 at a predetermined time interval such as once everyminute, or once every 5 minutes or once every 30 minutes or any othersuitable or desired programmable time interval to request analyterelated data from on body electronics 110. When data processing module160 receives the requested analyte related data, it stores the receiveddata. In this manner, analyte monitoring system 100 may be configured toreceive the continuously monitored analyte related information at theprogrammed or programmable time interval, which is stored and/ordisplayed to the user. The stored data in data processing module 160 maybe subsequently provided or transmitted to display device 120, remoteterminal 170 or the like for subsequent data analysis such asidentifying frequency of periods of glycemic level excursions over themonitored time period, or the frequency of the alarm event occurrenceduring the monitored time period, for example, to improve therapyrelated decisions. Using this information, the doctor, healthcareprovider or the user may adjust or recommend modification to the diet,daily habits and routines such as exercise, and the like.

In another embodiment, data processing module 160 transmits a command orsignal to on body electronics 110 to receive the analyte related data inresponse to a user activation of a switch provided on data processingmodule 160 or a user initiated command received from display device 120.In further embodiments, data processing module 160 is configured totransmit a command or signal to on body electronics 110 in response toreceiving a user initiated command only after a predetermined timeinterval has elapsed. For example, in certain embodiments, if the userdoes not initiate communication within a programmed time period, suchas, for example about 5 hours from last communication (or 10 hours fromthe last communication, or 24 hours from the last communication), thedata processing module 160 may be programmed to automatically transmit arequest command or signal to on body electronics 110. Alternatively,data processing module 160 may be programmed to activate an alarm tonotify the user that a predetermined time period of time has elapsedsince the last communication between the data processing module 160 andon body electronics 110. In this manner, users or healthcare providersmay program or configure data processing module 160 to provide certaincompliance with analyte monitoring regimen, so that frequentdetermination of analyte levels is maintained or performed by the user.

In certain embodiments, when a programmed or programmable alarmcondition is detected (for example, a detected glucose level monitoredby analyte sensor 101 that is outside a predetermined acceptable rangeindicating a physiological condition which requires attention orintervention for medical treatment or analysis (for example, ahypoglycemic condition, a hyperglycemic condition, an impendinghyperglycemic condition or an impending hypoglycemic condition)), theone or more output indications may be generated by the control logic orprocessor of the on body electronics 110 and output to the user on auser interface of on body electronics 110 so that corrective action maybe timely taken. In addition to or alternatively, if display device 120is within communication range, the output indications or alarm data maybe communicated to display device 120 whose processor, upon detection ofthe alarm data reception, controls the display 122 to output one or morenotification.

In certain embodiments, control logic or microprocessors of on bodyelectronics 110 include software programs to determine future oranticipated analyte levels based on information obtained from analytesensor 101, e.g., the current analyte level, the rate of change of theanalyte level, the acceleration of the analyte level change, and/oranalyte trend information determined based on stored monitored analytedata providing a historical trend or direction of analyte levelfluctuation as function time during monitored time period. Predictivealarm parameters may be programmed or programmable in display device120, or the on body electronics 110, or both, and output to the user inadvance of anticipating the user's analyte level reaching the futurelevel. This provides the user an opportunity to take timely correctiveaction.

Information, such as variation or fluctuation of the monitored analytelevel as a function of time over the monitored time period providinganalyte trend information, for example, may be determined by one or morecontrol logic or microprocessors of display device 120, data processingmodule 160, and/or remote terminal 170, and/or on body electronics 110.Such information may be displayed as, for example, a graph (such as aline graph) to indicate to the user the current and/or historical and/orand predicted future analyte levels as measured and predicted by theanalyte monitoring system 100. Such information may also be displayed asdirectional arrows (for example, see trend or directional arrow display131) or other icon(s), e.g., the position of which on the screenrelative to a reference point indicated whether the analyte level isincreasing or decreasing as well as the acceleration or deceleration ofthe increase or decrease in analyte level. This information may beutilized by the user to determine any necessary corrective actions toensure the analyte level remains within an acceptable and/or clinicallysafe range. Other visual indicators, including colors, flashing, fading,etc., as well as audio indicators including a change in pitch, volume,or tone of an audio output and/or vibratory or other tactile indicatorsmay also be incorporated into the display of trend data as means ofnotifying the user of the current level and/or direction and/or rate ofchange of the monitored analyte level. For example, based on adetermined rate of glucose change, programmed clinically significantglucose threshold levels (e.g., hyperglycemic and/or hypoglycemiclevels), and current analyte level derived by an in vivo analyte sensor,the system 100 may include an algorithm stored on computer readablemedium to determine the time it will take to reach a clinicallysignificant level and will output notification in advance of reachingthe clinically significant level, e.g., 30 minutes before a clinicallysignificant level is anticipated, and/or 20 minutes, and/or 10 minutes,and/or 5 minutes, and/or 3 minutes, and/or 1 minute, and so on, withoutputs increasing in intensity or the like.

Referring again back to FIG. 1, in certain embodiments, softwarealgorithm(s) for execution by data processing module 160 may be storedin an external memory device such as an SD card, microSD card, compactflash card, XD card, Memory Stick card, Memory Stick Duo card, or USBmemory stick/device including executable programs stored in such devicesfor execution upon connection to the respective one or more of the onbody electronics 110, remote terminal 170 or display device 120. In afurther aspect, software algorithms for execution by data processingmodule 160 may be provided to a communication device such as a mobiletelephone including, for example, WiFi or Internet enabled smart phonesor personal digital assistants (PDAs) as a downloadable application forexecution by the downloading communication device.

Examples of smart phones include Windows®, Android™, iPhone® operatingsystem, Palm® WebOS™, Blackberry® operating system, or Symbian®operating system based mobile telephones with data network connectivityfunctionality for data communication over an internet connection and/ora local area network (LAN). PDAs as described above include, forexample, portable electronic devices including one or moremicroprocessors and data communication capability with a user interface(e.g., display/output unit and/or input unit, and configured forperforming data processing, data upload/download over the internet, forexample. In such embodiments, remote terminal 170 may be configured toprovide the executable application software to the one or more of thecommunication devices described above when communication between theremote terminal 170 and the devices are established.

In still further embodiments, executable software applications may beprovided over-the-air (OTA) as an OTA download such that wiredconnection to remote terminal 170 is not necessary. For example,executable applications may be automatically downloaded as softwaredownload to the communication device, and depending upon theconfiguration of the communication device, installed on the device foruse automatically, or based on user confirmation or acknowledgement onthe communication device to execute the installation of the application.The OTA download and installation of software may include softwareapplications and/or routines that are updates or upgrades to theexisting functions or features of data processing module 160 and/ordisplay device 120.

Referring back to remote terminal 170 of FIG. 1, in certain embodiments,new software and/or software updates such as software patches or fixes,firmware updates or software driver upgrades, among others, for displaydevice 120 and/or on body electronics 110 and/or data processing module160 may be provided by remote terminal 170 when communication betweenthe remote terminal 170 and display device 120 and/or data processingmodule 160 is established. For example, software upgrades, executableprogramming changes or modification for on body electronics 110 may bereceived from remote terminal 170 by one or more of display device 120or data processing module 160, and thereafter, provided to on bodyelectronics 110 to update its software or programmable functions. Forexample, in certain embodiments, software received and installed in onbody electronics 110 may include software bug fixes, modification to thepreviously installed software parameters (modification to analyterelated data storage time interval, resetting or adjusting time base orinformation of on body electronics 110, modification to the transmitteddata type, data transmission sequence, or data storage time period,among others). Additional details describing field upgradability ofsoftware of portable electronic devices, and data processing areprovided in U.S. application Ser. Nos. 12/698,124, 12/794,721, now U.S.Pat. No. 8,595,607, Ser. No. 12/699,653, and 12/699,844, now U.S. Pat.No. 8,930,203, and U.S. Provisional Application Nos. 61/359,265, and61/325,155 the disclosure of which is incorporated by reference hereinfor all purposes.

Generally, the concentration of glucose in a person changes as a resultof one or more external influences such as meals and exercise, and alsochanges resulting from various physiological mechanisms such as stress,illness, menstrual cycle and the like. In a person with diabetes, suchchanges can necessitate monitoring the person's glucose level andadministering insulin or other glucose level altering drugs, such as,e.g., a glucose lowering or raising drug, as needed to maintain theperson's glucose level with a desired range. In any of the aboveexamples, the system 100 is thus configured to determine, based on someamount of patient-specific information, an appropriate amount, typeand/or timing of insulin or other glucose level altering drug toadminister in order to maintain normal glucose levels without causinghypoglycemia or hyperglycemia. In some embodiments, the system 100 isconfigured to control one or more external insulin pumps, such as, e.g.,subcutaneous, transcutaneous or transdermal pumps, and/or implantedinsulin pumps to automatically infuse or otherwise supply theappropriate amount and type of insulin to the user's body in the form ofone or more insulin boluses.

In another embodiment, the system 100 is configured to display orotherwise notify the user of the appropriate amount, type, and/or timingof the insulin in the form of an insulin delivery or administrationrecommendation or instruction. In such embodiments, the hardware and/orsoftware forming system 100 allows the user to accept the recommendedinsulin amount, type, and/or timing, or to reject it. If therecommendation is accepted by the user, the system 100, in oneembodiment, automatically infuses or otherwise provides the appropriateamount and type of insulin to the user's body in the form of one or moreinsulin boluses. If, on the other hand, the user rejects the insulinrecommendation, the hardware and/or software forming system 100 allowsthe user to override the system 100 and manually enter values forinsulin bolus quantity, type, and/or timing in the system 100. Thesystem 100 is thus configured by the user to automatically infuse orotherwise provide the user specified amount, type, and/or timing of theinsulin to the user's body in the form of one or more insulin boluses.

Alternatively, the appropriate amount and type of insulin correspondingto the insulin recommendation displayed by the system 100 may bemanually injected into, or otherwise administered to, the user's body.It will be understood, however, that the system 100 may alternatively oradditionally be configured in like manner to determine, recommend,and/or deliver other types of medication to a patient.

The system 100 is operable, as just described, to determine and eitherrecommend or administer an appropriate amount of insulin or otherglucose level lowering drug to the patient in the form of one or moreinsulin boluses. In order to determine appropriate amounts of insulin tobe delivered or administered to the user to bring the user's glucoselevel within an acceptable range, the system 100 requires at least someinformation relating to one or more external influences and/or variousphysiological mechanisms associated with the user. For example, thesystem 100 may receive information if the user is about to ingest, isingesting, or has recently ingested, a meal or snack, to determine anappropriate amount, type and/or timing of one or more meal compensationboluses of insulin. When a person ingests food in the form of a meal orsnack, the person's body reacts by absorbing glucose from the meal orsnack over time. For purposes of this document, any ingesting of foodmay be referred hereinafter as a “meal,” and the term “meal” thereforeencompasses traditional meals, such as, e.g., breakfast, lunch, anddinner, as well as intermediate snacks, drinks, and the like.

FIG. 2 depicts a typical glucose profile 200 for a user determined usinga CGM sensor, such as sensor 101 with on body electronics 110. The graph205 plots the measured glucose level as a function of time. This profileshows the effect on glucose level from various actions, such asmeal/carbohydrate intake 210, and the delivery of rapid acting insulin220 and long acting insulin 230.

The general shape of a glucose profile for any person rises followingingestion of a meal, peaks at some measureable time following the meal,and then decreases thereafter. The speed, e.g., the rate from beginningto completion, of any one glucose absorption profile typically variesfor a person by meal composition, meal type or time (e.g., breakfast,lunch, dinner, or snack), and/or according to one or more other factors,and may also vary from day-to-day under otherwise identical mealcircumstances. Generally, the information relating to such meal intakeinformation supplied by the user to the system 100 should contain,either explicitly or implicitly, an estimate of the carbohydrate contentof the meal or snack, corresponding to the amount of carbohydrates thatthe user is about to ingest, is ingesting, or has recently ingested, aswell as an estimate of the speed of overall glucose absorption from themeal by the user.

The estimate of the amount of carbohydrates that the patient is about toingest, is ingesting, or has recently ingested, may be provided by theuser in any of the various forms. Examples include, but are not limitedto, a direct estimate or carbohydrate weight (e.g., in units of grams orother convenient weight measure), an amount of carbohydrates relative toa reference amount (e.g., a dimensionless amount), an estimate of mealor snack size (e.g., a dimensionless amount or units of serving), and anestimate of meal or snack size relative to a reference snack size (e.g.,a dimensionless amount). Other forms of providing for user input ofcarbohydrate content of a meal or snack will occur to those skilled inthe art, and any such other forms are contemplated by this disclosure.

The estimate of the speed of overall glucose absorption from the meal bythe user may likewise be provided by the user in any of various forms.For example, for a specified value of the expected speed of overallglucose absorption, the glucose absorption profile captures the speed ofabsorption of the meal taken by the user. As another example, the speedof overall glucose absorption from the meal by the user also includestime duration between ingesting of the meal by a user and the peakglucose absorption of the meal by that user, which captures the durationof the meal taken by the user. The speed of overall glucose absorptionmay thus be expressed in the form of meal speed or duration. Examples ofthe expected speed of overall glucose absorption parameter in this casemay include, but are not limited to, a compound parameter correspondingto an estimate of the meal speed or duration (e.g., units of time), acompound parameter corresponding to meal speed or duration relative to areference meal speed or duration (e.g., dimensionless), or the like.

As another example of providing the estimate of the expected speed ofoverall glucose absorption parameter, the shape and duration of theglucose absorption profile may be mapped to the composition of the meal.Examples of the expected speed of overall glucose absorption parameterin this case may include, but are not limited to, an estimate of fatamount, protein amount, and carbohydrate amount (e.g., in units ofgrams) in conjunction with a carbohydrate content estimate in the formof meal size or relative meal size, an estimate of fat amount andcarbohydrate amount relative to reference fat, protein, and carbohydrateamounts in conjunction with a carbohydrate content estimate in the formof meal size or relative meal size, and an estimate of total glycemicindex of the meal or snack (e.g., dimensionless), wherein the term“total glycemic index” is defined for purposes of this disclosure as aparameter that ranks meals and snacks by the speed at which the meals orsnacks cause the user's glucose level to rise. Thus, for example, a mealor snack having a low glycemic index produces a gradual rise in glucoselevel whereas a meal or snack having a high glycemic index produces afast rise in glucose level. One exemplary measure of total glycemicindex may be, but is not limited to, the ratio of carbohydrates absorbedfrom the meal and a reference value, such as derived from pure sugar orwhite bread, over a specified time period (e.g., 2 hours). Other formsof providing for user input of the expected overall speed of glucoseabsorption from the meal by the patient, and/or for providing for userinput of the expected shape and duration of the glucose absorptionprofile generally will occur to those skilled in the art, and any suchother forms are contemplated by this disclosure.

Generally, the concentration of glucose in a person with diabeteschanges as a result of one or more external influences such as mealsand/or exercise, and may also change resulting from variousphysiological mechanisms such as stress, menstrual cycle and/or illness.In any of the above examples, the system 100 responds to the measuredglucose by determining the appropriate amount of insulin to administerin order to maintain normal glucose levels without causing hypoglycemia.In some embodiments, the system 100 is implemented as a discreet systemwith an appropriate sampling rate, which may be periodic, aperiodic, ortriggered, although other continuous systems or hybrid systems mayalternatively be implemented as described above.

As one example of a conventional diabetes control system, one or moresoftware algorithms may include a collection of rule sets which use (1)glucose information, (2) insulin delivery information, and/or (3) userinputs such as mean intake, exercise, stress, illness and/or otherphysiological properties to provide therapy, and the like, to manage theuser's glucose level. The rule sets are generally based on observationsand clinical practices as well as mathematical models derived through orbased on analysis of physiological mechanisms obtained from clinicalstudies. In the exemplary system, models of insulin pharmacokinetics,pharmacodynamics, glucose dynamics, meal absorption and exerciseresponses of individual patients are used to determine the timing andthe amount of insulin to be delivered. A learning module may be providedto allow adjustment of the model parameters when the patient's overallperformance metric degrades such as, for example, adaptive algorithms,using Bayesian estimates, may be implemented. An analysis model may alsobe incorporated which oversees the learning to accept or rejectlearning. Adjustments are achieved utilizing heuristics, rules,formulae, minimization of cost function(s) or tables (such as, forexample, gain scheduling).

Model-based methods, such as a Kalman filter, can be programmed into theprocessor(s) of the system using appropriate embedded or inputtedsoftware to predict the outcome of adding a controlled amount of insulinor other drug to a user in terms of the expected glucose value. Thestructures and parameters of the models define the anticipated behavior.

Any of a variety of conventional controller design methodologies, suchas PID (Proportional-Integral-Derivative) systems, full state feedbacksystems with state estimators, output feedback systems, LQG(Linear-Quadratic-Guassian) controllers, LQR(Linear-Quadratic-Regulator) controllers, eigenvalue/eigenstructurecontroller systems, and the like, could be used to design algorithms toperform physiological control. They typically function by usinginformation derived from physiological measurements and/or user inputsto determine the appropriate control action to use. While the simplerforms of fixed controllers use fixed parameters (and therefore rules)for computing the magnitude of control action, the parameters in moresophisticated forms of such controllers may use one of more dynamicparameters. The one or more dynamic parameters could, for example, takethe form of one or more continuously or discretely adjustable gainvalues. Specific rules for adjusting such gains could, for example, bedefined either on an individual basis or on the basis of a userpopulation, and in either case will typically be derived according toone or more mathematical models. Such gains are typically scheduledaccording to one or more rule sets designed to cover the expectedoperating ranges in which operation is typically nonlinear and variable,thereby reducing sources of error.

Model based control systems, such as those utilizing model predictivecontrol algorithms, can be constructed as a black box wherein equationsand parameters have no strict analogs in physiology. Rather, such modelsmay instead be representations that are adequate for the purpose ofphysiological control. The parameters are typically determined frommeasurements of physiological parameters such as glucose level, insulinconcentration, and the like, and from physiological inputs such as foodintake, alcohol intake, insulin dose, and the like, and also fromphysiological states such as stress level, exercise intensity andduration, menstrual cycle phase, and the like. These models are used toestimate current glucose level or to predict future glucose levels. Suchmodels may also take into account unused insulin remaining in the userafter a bolus of insulin is given, for example, in anticipation of ameal. Such unused insulin will be variously described as unused,remaining, or “insulin on board.”

A model based control system can perform a prediction of a user's bloodglucose concentration in terms of a “best-estimate” as well as upperand/or lower bounds of the estimate for the present time and up to afinite time in the future. A Kalman filter can be implemented by themodel based control system to estimate, predict, and model thebest-estimate and the variance (i.e., upper and/or lower bounds) of auser's blood analyte concentration. A Kalman filter produces estimatesof the true values of measurements of the user's blood glucoseconcentration by predicting a value, estimating the uncertainty of thepredicted value, and computing a weighted average of the predicted valueand the measured value. The most weight is given to the value with theleast uncertainty. The estimates produced by the Kalman filter tend tobe closer to the true values than the original measurements because theweighted average has a better estimated uncertainty than either of thevalues that went into the weighted average. The Kalman filter modelassumes the true state at time k is evolved from the state at (k−1)according to x_(k)=F_(k)x_(k-1)+B_(k)u_(k)+w_(k), where:

-   -   F_(k) is the state transition model which is applied to the        previous state x_(k-1);    -   B_(k) is the control-input model which is applied to the control        vector u_(k);    -   w_(k) is the process which is assumed to be drawn from a zero        mean multivariate normal distribution with covariance Q_(k).

The Kalman filter is a recursive estimator, which means that only theestimated state from the previous time step and the current measurementare needed to compute the estimate for the current state. In contrast tobatch estimation techniques, no history of observations and/or estimatesis required. In what follows, the notation {circumflex over (x)}_(n|m)represents the estimate of x at time n given observations up to, andincluding time m. The state of the filter is represented by twovariables:

-   -   1. {circumflex over (x)}_(n|m), the a posteriori state estimate        at time k given observations up to and including time k; and    -   2. P_(k|k), the a posteriori error covariance matrix (e.g., a        measure of the estimated accuracy of the state estimate.

The Kalman filter can be written as a single equation; however it ismost often conceptualized as two distinct phases: “predict” and“update.” The predict phase uses the state estimate from the previoustimestep to produce an estimate of the state at the current timestep.The predicted state estimate is also known as the a priori stateestimate because, although it is an estimate of the state at the currenttimestep, it does not include observation information from the currenttimestep. In the update phase, the current a priori prediction iscombined with current observation information to refine the stateestimate. The improved estimate is termed the a posteriori stateestimate. Typically, the two phases alternate, with the predictionadvancing the state until the next scheduled observation, and the updateincorporating the observation. However, this is not necessary. If anobservation is unavailable for some reason, the update may be skippedand multiple prediction steps performed. Likewise, if multipleindependent observations are available at the same time, multiple updatesteps may be performed. The formula for the updated estimate andcovariance of the Kalman filter can be seen below.{circumflex over (x)} _(k|k-1) =F _(k) {circumflex over (x)} _(k-1|k-1)+B _(k) u _(k);  Predicted (i.e., a priori) state estimate:P _(k|k-1) =F _(k) P _(k=−1|k-1) F _(k) ^(T) +Q _(k);  Predicted (i.e.,a priori) estimate covariance:y=z _(k) −H _(k) {circumflex over (x)} _(k|k-1);  Measurement residual:S _(k) =H _(k) P _(k|k-1) H _(k) ^(T) +R _(k);  Residual covariance:K _(k) =P _(k|k-1) H _(k) ^(T) S _(k) ⁻¹;  Optimal Kalman Gain:{circumflex over (x)} _(k|k) ={circumflex over (x)} _(k|k-1) +K _(k) ŷ_(k); and  Updated (i.e., a posteriori) state estimate:P _(k|k)=(I−K _(k) H _(k))P _(k|k-1).  Updated (i.e., a posteriori)estimate covariance:

More specifically, the Kalman filter of the model based control systemcan use the known user inputs described above and the user's bloodanalyte readings taken from the on-body sensor to determine abest-estimate of the user's actual blood analyte readings.

Insulin therapy is derived by the system based on the model's ability topredict glucose levels for various inputs. Other conventional modelingtechniques may be additionally or alternatively used to predict glucoselevels, including for example, but not limited to, building models fromfirst principles.

In a system as described above, the controller is typically programmedto provide a “basal rate” of insulin deliver or administration. Such abasal rate is the rate of continuous supply of insulin by an insulindelivery device such as a pump that is used to maintain a desiredglucose level in the user. Periodically, due to various events thataffect the metabolism of a user, such as eating a meal or engaging inexercise, a “bolus” delivery of insulin is required. A “bolus” isdefined as a specific amount of insulin that is required to raise theblood concentration of insulin to an effective level to counteract theeffects of the ingestion of carbohydrates during a meal and also takesinto account the effects of exercise on the glucose level of the user.

As described above, an analyte monitor may be used to continuouslymonitor the glucose level of a user. The controller is programmed withappropriate software and uses models as described above to predict theeffect of carbohydrate ingestion and exercise, among other factors, onthe predicted level of glucose of the user at a selected time. Such amodel must also take into account the amount of insulin remaining in theblood stream from a previous bolus or basal rate infusion of insulinwhen determining whether or not to provide a bolus of insulin to theuser.

Continuous glucose monitoring (CGM) systems occasionally exhibitnon-zero-mean signal artifacts commonly called “dropout,” where thesensor signal output is momentarily lower than it should be given aninterstitial glucose value. From a closed-loop control perspective, thismeasurement error poses an annoyance in that the falsely lower signalcould trigger a momentary reduction or cessation of insulin deliverycommands due to the perceived hypoglycemic event. This can result in afalse alarm based either on a perceived current glucose level or acomputed future glucose level.

In certain embodiments of the present disclosure, techniques includingcomputer implemented algorithms for reducing false hypoglycemic alarmsdue to a combination of a user's glucose range being mostly euglycemic(normal) and CGM system signal artifacts such as dropouts which tend tonegatively bias the glucose display is provided. In such embodiments,the threshold for detecting a hypoglycemic threshold is modified byintroducing a conditional time delay such that most dropouts are shorterin duration than the time delay so that the dropouts do not trigger analarm. Additionally, the threshold is modified appropriately so thatdetection of true hypoglycemic events is not delayed beyond what hasbeen determined to be clinically safe.

It is possible, using clinical data and insulin delivery information, totrust a CGM system to provide a balance between hypoglycemic detectionsensitivity and reasonable specificity that minimizes false alarms undera wide range of glucose profiles. With good glycemic control, theproportion of true-hypoglycemia may be reduced significantly enough thatsignal artifacts of the CGM system become an important factor in causingfalse alarm rates.

In one embodiment of the present system, a combination of glucose levelmeasurements, known as CGM signal artifact characteristics, and thebest-estimate of relevant physiological states, such as, for example,plasma glucose, interstitial glucose, insulin on board, and effectiveinsulin, are used to delay the enunciation of a CGM based hypoglycemicalarm and determine whether or not the alarm should persist. In thisembodiment, instead of using an artifact detector which relies on amechanism that is sensitive to the artifacts in the signal, the alarminstead is tuned to be insensitive to the artifacts, yet at the sametime maintain a safe level of sensitivity to hypoglycemic events.

The CGM based hypoglycemic alarm of the one embodiment of the disclosurecomprises several hypoglycemic thresholds. For each threshold, thereexists a timer that may potentially annunciate a hypoglycemic alarm. Thelower the threshold, the shorter the amount of delay between the timethe CGM measurement value is obtained and when the alarm is sounded. Theamount of delay depends primarily on the level of risk associated withthe delayed response to a true hypoglycemic event at a given glucoselevel as well as the probability of the duration of false alarms due tothe presence of CGM signal artifacts at a given glucose level.

The CGM based hypoglycemic alarm may result in the system recommendingthat a finger stick glucose level measurement request. If the glucoselevel measurement resulting from the finger stick indicates that the CGMmeasure hypoglycemia does not exist, the system can turn off the alarm.Alternatively, if the finger stick glucose level measurement confirmsthe presence of hypoglycemia, then the controller may indicate to theuser that certain actions, such as taking rescue carbohydrates and/orchecking glucose level frequently thereafter until the condition hasbeen resolved, may be required.

A user with a well-controlled glucose level, using either a fullyautomatic closed loop system, a partial closed loop system or intensiveopen loop treatment, may have a glucose profile and distribution that isaltered enough that the amount of false hypoglycemic alarms from thesystem is significantly larger than found in the general population ofclinical data used to tune and confirm the hypoglycemic alarm response.The primary reason for this is that in the lower glucose range, theeffect of signal artifacts from the CGM device become more dominant.

The CGM signal artifacts that reduce the effectiveness of the CGM basedhypoglycemic alarm have been found to have an a priori distribution ofseverity, duration, and trajectory profile. Given a user's history ofglucose levels, insulin delivery, and other relevant physiologicalinformation, a particular level of hypoglycemia carries a particularlevel of risk in terms of the maximum delay allowed before treatmentshould begin to avoid the effects of sever hypoglycemia. Delaying ahypoglycemic alarm to the extent that it is still clinically safe andyet as long as possible can reduce the false alarms due to the CGMsignal artifacts.

Given a glucose level confirmation and possibly a corrective action suchas administering rescue carbohydrates, glucose can be estimated withsufficient confidence such that for a finite horizon in the future,there is no need to activate the CGM based hypoglycemic alarm. Thisfurther decreases the likelihood of false alarms.

In one embodiment of the disclosure, the controller is programmed usingappropriate software so as to set up two separate subsystems fordecision making. While these subsystems will be described in terms ofone or more state machines, those skilled in the art of control theoryand engineering will understand that other embodiments may becontemplated. Thus, skilled artisans will understand how to program theprocessor to implement such a state machine.

FIG. 3 illustrates a state machine which governs the behavior of theassertion of the CGM based hypoglycemic detector. FIG. 3 also depicts astate machine which governs how and when confirmatory glucose levelmeasurements, such as by a finger stick, should be taken, how and whenrescue carbohydrates should be administered, and when to de-assert theCGM based hypoglycemic detector.

Referring now to FIG. 3, in certain embodiments the CGM state machine isconfigured to determine when a hypoglycemic alarm should be assertedrelative to a CGM threshold reading and a best-estimate of the user's BGconcentration that is determined by the system. The CGM state machinebegins at 105. When the CGM measurements become available, the statemachine enters the “no hypoglycemia confirmed” state 110. Within thisstate, the controller obtains a current CGM value and also obtains abest-estimate of the user's blood glucose value, and dependent on thevalue of the measurements, controls the analysis along one of severalpaths. For example, if the latest CGM value (i.e., the CGM 115) is lessthan or equal to 3.5 mMol/L (63 mg/dL) but greater than 3.0 mMol/L (54mg/dL), but the best-estimate determines that the BG concentration isabove 3.5 mMol/L a delay timer of 40 minutes is implemented at state120. If the detected CGM value is greater than 2.5 mMol/L (45 mg/dL) butless than or equal to 3.0 mMol/L (54 mg/dL), but the best-estimatedetermines that the BG concentration is above 3.5 mMol/L a delay of 30minutes is implemented at state 125. Similarly, if the detected CGMvalue is greater than 2.0 mMol/L (36 mg/dL) but less than or equal to2.5 mMol/L (45 mg/dL), but the best-estimate determines that the BGconcentration is above 3.5 mMol/L a delay of 20 minutes is implementedat state 130.

When any of the timer set at states 120, 125, or 130 expire, and thelatest CGM value is still no higher than the corresponding upper limitsfor the delayed timer module states 120, 125, or 130, the state changesto “confirm intermediate hypoglycemia” at state 140. In this state, thecontroller resets all the timers of states 120, 125, and 130, and setsthe hypoglycemia alarm to on. This state prevents the alarm fromsounding unnecessarily when a user's glucose level is still within arange where the annoyance of an alarm outweighs the risk that the useris actually in a hypoglycemic condition that requires immediateattention. Once the alarm is sounded, the CGM state machine returns tothe “no confirmed hypoglycemia” state 110.

Where the detected CGM value is less than or equal to 2.0 mMol/L (36mg/dL), which is indicative of severe hypoglycemia, no delay isimplemented, and the machine exits from the “no confirmed hypoglycemia”state 110 to state 145. In this state, all of the timers of states 120,125, and 130 are reset, the hypoglycemia alarm is set to on, thussounding an alarm, and the controller continues to check the current CGMvalue and the best-estimate value. In this state the system cannotreturn to the “no confirmed hypoglycemia” state 110 until the latest CGMvalue rises above 3.5 mMol/L (63 mg/dL). The hypoglycemia alarm, whichwas already activated, is related to the glucose level subsystem. Whenthe latest CGM value rises above 3.5 mMol/L, the CGM subsystem statemachine returns to “no confirmed hypoglycemia” state 110, whether or notthe latest alarm has been confirmed by a separate glucose level reading.

Referring now to FIG. 4, the controller is programmed to set up aseparate blood glucose (BG) level subsystem, which will be described interms of a state machine. This state machine de-asserts the hypoglycemicalarm upon non-hypoglycemic confirmation using a glucose level at afixed threshold and/or a best-estimate of the glucose level, such aswhen the glucose level is equal and/or estimated to 3.5 mMol/L (63mg/dL). When the system starts, the BG state machine initializes intostate 205. In this state, no glucose level check is needed, and thehypoglycemia alarm is set to off.

When the CGM state machine asserts the hypoglycemic alarm at states 140or 145, the BG state machine performs a transition 207, where the BGstate machine enters a “BG check needed” state 210. In this state, thesystem requests and waits for a finger stick glucose level measurementat 215, and if a “BG equals hypoglycemia” confirmation results from thefinger stick, the controller alerts the user at state 220. Thehypoglycemia confirmation based on the BG finger stick may be set at theuppermost limit of the CGM state machine's limits, which may be equal to3.5 mMol/L (63 mg/dL) as depicted in FIG. 2, or any other suitablevalue. The user may then address the low glucose level measurement bytaking rescue carbohydrates at state 220. This action may be recommendedby the controller. The controller also requests another glucose level bemeasured in 15 minutes. This process continues until the latest glucoselevel indicates that the user is no longer in a hypoglycemic state.

The previous embodiments illustrated in FIGS. 3 and 4 may be generalizedfurther by removing the actions “confirm intermediate hypoglycemia”(FIG. 3, reference number 140) and “confirm severe hypoglycemia” (FIG.3, reference number 145) from the CGM state machine. In this embodiment,no CGM hypoglycemia timers are reset until the timers expire and thehypoglycemia alarm is annunciated. This allows for several alarmmechanisms to occur simultaneously.

In certain embodiments, if the current CGM glucose value rises above 3.5mMol/L at any time while the CGM state machine is in the “no confirmedhypoglycemia” state 110, the alarm may be reset and the controllerreturns to processing incoming CGM data as before. In this case, noalarm will be sounded.

Referring now to FIG. 5A and FIG. 5B, another embodiment utilizes priorknowledge of various factors such as glucose level, CGM value, insulinon board, and the like, to further minimize false alarms by modifyingthe length of the delay timer if there is a convergence in theinformation gathered from the CGM sensor and the best-estimate of theuser's BG level. As in the embodiment depicted in FIG. 3, the CGM statemachine asserts the hypoglycemic alarm, and the BG state machinede-asserts the alarm. However, the two state machines are coupled evenfurther with the assumption that while the system is set at a“hypoglycemia suspected” state 340, no CGM based hypoglycemic thresholdshall matter. In addition, depending on the control model and the valuefrom the latest finger stick glucose level check, a variable time can beadded to delay the return into the periodic CGM based hypoglycemicdetection “no hypoglycemia suspected” state 310.

For example, if the latest finger stick BG value is 4.0 mMol/L (72mg/dL), and the control model predicts a rapidly rising glucose level,then a relatively short delay timer might be activated before the systemtransitions from “hypoglycemia suspected” state 340 to the “nohypoglycemia suspected” state 310. On the other hand, if the latestfinger stick BG check indicates a glucose level value of 4.0 mMol/L (72mg/dL) and the control model programmed into the controller predicts arapidly dropping glucose level profile, then the system immediatelytransitions from the “hypoglycemia suspected” state 340 to “nohypoglycemia suspected” state 310, but the CGM based hypoglycemiadetector will be given the fastest opportunity to trigger. Using thecontrol model and relative value of the latest finger stick BG checkallows the system to apply a state transition rule that is decoupledfrom which CGM based hypoglycemic detector triggered the statetransition, thus preventing false hypoglycemia alarms.

Referring to FIG. 5B, when the “hypoglycemia suspected” state 340 isentered, a finger stick BG value is requested at state 345. Depending onthe glucose level profile of the user, that is, the profile due to priorinsulin deliveries, insulin sensitivity, exercise and the like, thecontroller may enter either state 355, where rescue carbohydrates areadministered and the finger stick BG is again measured after fifteenminutes, or state 350, where a timer indicating when the next fingerstick BG confirmation is to be performed is started. The duration ofthis timer is dependent upon a determination of the likelihood ofglucose value changes based on the future glucose level profiledetermined by the control model being used by the controller and thelatest finger stick glucose level value.

In this embodiment, the system checks the CGM value at every sampletime, instead of using four or more distinct hypoglycemia thresholdswith specific time delay amounts, and continues to count-down the timeruntil it is larger than a latest-glucose-dependent timer.

In certain embodiments, a table of delay values as a function of glucoselevel is used by the processor to modify the timer delay, where crossinga lower glucose value results in a shorter alarm delay. An alarm will beannunciated whenever any timer expires (e.g., the glucose value remainsbelow that threshold value for the duration of the timer delay). Table 1below depicts a table that can be used by the processor to modify thetimer delay.

TABLE 1 Table implemented by the processor to determine the timer delaybased upon a user's glucose concentration. Glucose Concentration (mg/dL)Time (minutes) 60 30 50 15 45 0

For example, if the CGM sensor detects a drop in the user's bloodglucose concentration to a hypoglycemic level, but the best-estimatepredicts that the user's blood glucose is at a euglycemic level, thenthe likelihood of an actual hypoglycemic event is low. Various reasonscould cause such a divergence, such as a CGM calibration error or CGMsignal distortion errors such as night-time drop outs. When the user'sglucose level falls below 60 mg/dL, but is above 50 mg/dL, the alarmwill be delayed for 30 minutes. When the CGM sensor detects a glucoselevel between 50 mg/dL and 45 mg/dL, the alarm is delayed 15 minutesprior to annunciating. If the user's glucose level falls below 45 mg/dL,then the alarm annunciates immediately.

However if there is agreement between the user's blood glucoseconcentration determined by the CGM sensor and the best-estimateprediction that a hypoglycemic event is likely, then the system canmodify the alarm mechanism to thereby decrease the likelihood ofimposing unnecessary risk to the user. As the likelihood of ahypoglycemic event increases to a higher risk, the mechanism describedabove with respect to Table 1 can be implemented with a 50% shorteningof the alarm delay, as seen below in Table 2. In this embodiment, thealarm delay is shortened to 15 minutes when the detected CGM valuecrosses the 60 mg/dL threshold. The alarm delay is shortened to 7.5minutes when the detected CGM value crosses the 50 mg/dL threshold.However, the alarm is still annunciated immediately when the detectedCGM value crosses the 45 mg/dL threshold.

TABLE 2 Table implemented by the processor with a shortened alarm delaybased upon an increased risk of a hypoglycemic event. GlucoseConcentration (mg/dL) Time (minutes) 60 15 50 7.5 45 0

In certain embodiments, as the likelihood of a hypoglycemic eventincreases, the same delay times as seen in Table 1 are retained, but thethreshold values for blood analyte concentration are increased. Forexample, Table 3 illustrates that the alarm delay is set for 30 minuteswhen the detected CGM value crosses the 65 mg/dL threshold, that thealarm delay is set for 15 minutes when the detected CGM value crossesthe 55 mg/dL threshold, and the alarm is annunciated immediately whenthe detected CGM value crosses the 50 mg/dL threshold.

TABLE 3 Table implemented by the processor with an increased bloodglucose concentration based upon an increased risk of a hypoglycemicevent. Glucose Concentration (mg/dL) Time (minutes) 65 30 55 15 50 0

In certain embodiments, a hybrid between the two previously describedembodiments is implemented, wherein both threshold values and timedelays are adjusted if the best-estimate glucose range determined by themodel determines a heightened risk of a hypoglycemic event. As seen inTable 4 below, both the glucose threshold and the time delay aremodified to avoid imposing unnecessary risk to the user.

TABLE 4 Table implemented by the processor with an increased bloodglucose concentration and shortened alarm delay based upon an increasedrisk of a hypoglycemic event. Glucose Concentration (mg/dL) Time(minutes) 65 15 55 7.5 50 0

In further embodiments, the same principles of the previous threeembodiments can be applied to hyperglycemia detection, such that thetiered thresholds increase in the order of the threshold values. Forexample, if the information received from the analyte sensor and thebest-estimate of the user's analyte concentration are in divergence withone another the system waits 30 minutes when the detected CGM valuereaches a 180 mg/dL threshold and remains at that threshold beforetriggering the alarm, the system waits 15 minutes when the detected CGMvalue crosses a 200 mg/dL threshold and remains at that threshold beforetriggering the alarm, and the system waits 7.5 minutes once the detectedCGM value reaches a 220 mg/dL threshold and remains at that thresholdbefore triggering the alarm. However, as illustrated below in Table 5,if there is convergence between the data received from the detected CGMvalue and the best-estimate of the user's blood glucose concentration,then the system can modify one or both of the glucose concentrationthreshold and the length of time the system waits before asserting thehyperglycemia alarm.

TABLE 5 Table implanted by the processor with a decrease in thehyperglycemic alarm delay based upon an increased risk of ahyperglycemic event. Glucose Concentration (mg/dL) Time (minutes) 180 15200 7.5 220 3.75

The embodiments described above are particularly useful in reducing oreliminating unnecessary risk to a user by implementinghypoglycemic/hyperglycemic alarms in a timely manner. While severalspecific embodiments have been illustrated and described, it will beapparent that various modifications can be made without departing fromthe spirit and scope of the disclosure. Accordingly, it is not intendedthat the disclosure be limited, except as by the appended claims.

In certain embodiments, a computer-implemented method for determiningwhen to activate an alarm of a continuous analyte monitor may comprisereceiving, at a data processing component, information from thecontinuous analyte monitor related to the user's analyte concentration,determining, at the data processing component, the user's analyteconcentration using the information received from the continuous analytemonitor, receiving, at a data processing component, information from theuser related to the user's analyte concentration, determining, at a dataprocessing component, a best-estimate of the user's analyteconcentration based upon the information from the continuous analytemonitor and information from the user, determining, at a data processingcomponent, at least one condition for activating the alarm, andmodifying, at a data processing component, the at least one conditionfor activating the alarm based on a comparison between the determinationof the user's analyte concentration and the best-estimate of the user'sanalyte concentration.

Certain aspects may include that a best-estimate of the user's analyteconcentration includes a range of variance.

Certain aspects may include activating, at the processor, the analytealarm if at least one of the data signal related to the user's analyteconcentration satisfies the at least one determined condition.

Certain aspects may include that the best-estimate of the user's analyteconcentration is at least partially determined using at least one of aKalman filter and other state observers.

Certain aspects may include that the at least one condition foractivating the analyte alarm includes receiving a data signal thatindicates that the user's analyte concentration has reached a thresholdvalue.

Certain aspects may include that the at least one condition includesthat the user's analyte concentration crosses a threshold value for apredetermined length of time.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration are in high agreement with eachother, this suggests an increased likelihood of true physiologicalevents such as a hypoglycemic event.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration are in high agreement with eachother, this suggests an increased likelihood of a true physiologicalevents such as a hyperglycemic event.

Certain aspects may include that the modification includes increasing ordecreasing the threshold value of the user's analyte concentration.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration suggests an increased likelihood ofa hypoglycemic event, the threshold value is increased, and wherein whenthe comparison between the determination of the user's analyteconcentration and the best-estimate of the user's analyte concentrationsuggests a low likelihood of a hypoglycemic event, the threshold valueis decreased.

Certain aspects may include that the modification includes increasing ordecreasing the predetermined duration that the user's analyteconcentration may cross the threshold value.

Certain aspects may include that the modification includes increasing ordecreasing the threshold value for the user's analyte concentration, andincludes increasing or decreasing the predetermined duration that theuser's analyte concentration may cross the threshold value.

Certain aspects may include that the information from the continuousanalyte monitor includes at least one data signal.

In certain embodiments, an integrated analyte monitoring device assemblymay comprise an analyte sensor for transcutaneous positioning through askin layer and maintained in fluid contact with an interstitial fluidunder the skin layer during a predetermined time period, the analytesensor having a proximal portion and a distal portion, and sensorelectronics coupled to the analyte sensor that may comprise a circuitboard having a conductive layer and a sensor antenna disposed on theconductive layer, one or more electrical contacts provided on thecircuit board and coupled with the proximal portion of the analytesensor to maintain continuous electrical communication, and a dataprocessing component provided on the circuit board and in signalcommunication with the analyte sensor, the data processing componentconfigured to execute one or more routines for processing signalsreceived from the analyte sensor, the data processing componentconfigured to control the transmission of data associated with theprocessed signals received from the analyte sensor to a remote locationusing the sensor antenna in response to a request signal received fromthe remote location, the data processing component configured to receiveinformation from the continuous analyte monitor related to the user'sanalyte concentration, the data processing unit configured to determinethe user's analyte concentration using the information received from thecontinuous analyte monitor, the data processing component configured toreceive data from the user related to the user's analyte concentration,the data processing component configured to determine a best-estimate ofthe user's analyte concentration based upon the information receivedfrom the continuous analyte monitor and the data received from the userat the processor, the data processing component configured to determineat least one condition for activating an alarm, the data processingcomponent configured to modify the at least one condition for activatingthe alarm based on a comparison between the determination of the user'sanalyte concentration and the best-estimate of the user's analyteconcentration.

Certain aspects may include that the best-estimate of the user's analyteconcentration includes a range of variance.

Certain aspects may include that the data processing component isfurther configured to activate the alarm if at least one of the datasignals related to the user's analyte concentration and thebest-estimate of the user's analyte concentration satisfies the at leastone determined condition.

Certain aspects may include that the best-estimate of the user's analyteconcentration is at least partially determined using at least one of aKalman filter and other state observers.

Certain aspects may include that the at least one condition foractivating the alarm includes receiving a data signal that indicatesthat the user's glucose concentration has reached a threshold value.

Certain aspects may include that the at least one condition includesthat the user's analyte concentration crosses a threshold value for apredetermined length of time.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration are in high agreement with eachother, this suggests an increased likelihood of a hypoglycemic event.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration are in high agreement with eachother, this suggests an increased likelihood of true physiologicalevents such as a hyperglycemic event.

Certain aspects may include that the modification includes increasing ordecreasing the threshold value of the user's glucose concentration.

Certain aspects may include that when the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration suggests an increased likelihood ofa hypoglycemic event, the threshold value is increased, and wherein whenthe comparison between the determination of the user's analyteconcentration and the best-estimate of the user's analyte concentrationsuggests a low likelihood of a hypoglycemic event, the threshold valueis decreased.

Certain aspects may include that the modification includes increasing ordecreasing the predetermined duration that the user's analyteconcentration may cross the threshold value.

Certain aspects may include that the modification includes increasing ordecreasing the threshold value for the user's analyte concentration, andincludes increasing or decreasing the predetermined length of time thatthe user's analyte concentration may cross the threshold value.

Certain aspects may include that the information from the continuousanalyte monitor includes at least one data signal.

In some embodiments, an integrated analyte monitoring device maycomprise a data processing component provided on a circuit board and insignal communication with a continuous analyte monitor that may beconfigured to execute one or more routines for processing signalsreceived from the continuous analyte monitor, control the transmissionof data associated with the processed signals received from thecontinuous analyte monitor to a remote location using an antenna inresponse to a request signal received from the remote location, receiveinformation from the continuous analyte monitor related to the user'sanalyte concentration, determine the user's analyte concentration usingthe information received from the continuous analyte monitor, receivedata from the user related to the user's analyte concentration,determine a best-estimate of the user's analyte concentration based uponthe information received from the continuous analyte monitor and thedata received from the user at the processor, determine at least onecondition for activating an alarm, and modify the at least one conditionfor activating the alarm based on the comparison between thedetermination of the user's analyte concentration and the best-estimateof the user's analyte concentration.

While the present disclosure has been described with reference to thespecific embodiments thereof, it should be understood by those skilledin the art that various changes may be made and equivalents may besubstituted without departing from the true spirit and scope of thepresent disclosure. In addition, many modifications may be made to adapta particular situation, material, composition of matter, process,process step or steps, to the objective, spirit and scope of the presentdisclosure. All such modifications are intended to be within the scopeof the claims appended hereto.

What is claimed is:
 1. A method, comprising: receiving, at a dataprocessing component, information from a continuous analyte monitorrelated to a user's analyte concentration; determining, at the dataprocessing component, the user's analyte concentration using theinformation received from the continuous analyte monitor; determining,at the data processing component, a best-estimate of the user's analyteconcentration using the information received from the continuous analytemonitor; determining, at the data processing component, that the analyteconcentration and the best-estimate are in agreement; and modifying, atthe data processing component, at least one condition for activating analarm based on the determination that the analyte concentration and thebest-estimate are in agreement.
 2. The method of claim 1, wherein thebest-estimate of the user's analyte concentration includes a range ofvariance.
 3. The method of claim 2, wherein the best-estimate of theuser's analyte concentration is at least partially determined using aKalman filter.
 4. The method of claim 1, further comprising providing amedical recommendation associated with the analyte concentration to theuser.
 5. The method of claim 4, wherein providing the medicalrecommendation comprises displaying a recommended action for the user totake on a user interface.
 6. The method of claim 1, further comprisingdetermining, at the data processing component, that the at least onecondition is met using the information from the continuous analytemonitor, and activating, at the data processing component, the alarmwhen the at least one condition is met.
 7. The method of claim 1,wherein the at least one condition includes at least that the user'sanalyte concentration remains at or over a threshold value for apredetermined period of time.
 8. The method of claim 1, furthercomprising determining, at the data processing component, that when theanalyte concentration and the best-estimate are in agreement, that anincreased likelihood of a hypoglycemic event exists.
 9. The method ofclaim 1, wherein the continuous analyte monitor comprises a continuousanalyte sensor having a plurality of electrodes including a workingelectrode comprising an analyte-responsive enzyme bonded to a polymerdisposed on the working electrode.
 10. The method of claim 1, whereinthe continuous analyte monitor comprises a continuous analyte sensorhaving a plurality of electrodes including a working electrodecomprising a mediator bonded to a polymer disposed on the workingelectrode.
 11. A system, comprising: a continuous analyte sensorconfigured to be in contact with bodily fluid under a skin layer of auser to monitor a concentration of an analyte; and a data processingdevice comprising a data processing component, configured to: receiveinformation corresponding to the monitored concentration of the analyte;determine the user's analyte concentration using the receivedinformation corresponding to the monitored concentration of the analyte;determine a best-estimate of the user's analyte concentration using theinformation corresponding to the monitored concentration of the analyte;determine that the analyte concentration and the best-estimate are inagreement; and modify at least one condition for activating an alarmbased on the determination that the analyte concentration and thebest-estimate are in agreement.
 12. The system of claim 11, wherein thebest-estimate of the user's analyte concentration includes a range ofvariance.
 13. The system of claim 12, wherein the best-estimate of theuser's analyte concentration is at least partially determined using aKalman filter.
 14. The system of claim 13, wherein the data processingdevice is further configured to provide a medical recommendationassociated with the analyte concentration to the user.
 15. The system ofclaim 14, wherein the data processing device is configured to providethe medical recommendation by at least displaying a recommended actionfor the user to take on a user interface.
 16. The system of claim 11,wherein the data processing device is further configured to determinethat the at least one condition is met using the informationcorresponding to the monitored concentration of the analyte, and toactivate the alarm when the at least one condition is met.
 17. Thesystem of claim 11, wherein the at least one condition includes at leastthat the user's analyte concentration remains at or over a thresholdvalue for a predetermined period of time.
 18. The system of claim 11,wherein the data processing device is further configured to determinethat when the analyte concentration and the best-estimate are inagreement, that an increased likelihood of a hypoglycemic event exists.19. The system of claim 11, wherein the continuous analyte sensorcomprises a plurality of electrodes including a working electrodecomprising an analyte-responsive enzyme bonded to a polymer disposed onthe working electrode.
 20. The system of claim 11, wherein thecontinuous analyte sensor comprises a plurality of electrodes includinga working electrode comprising a mediator bonded to a polymer disposedon the working electrode.